Precision Engineering of 2D Protein Layers as Chelating Biogenic Scaffolds for Selective Recovery of Rare-Earth Elements.
Roger M PallaresMarimikel CharrierSara Tejedor-SanzDong LiPaul D AshbyCaroline M Ajo-FranklinCorie Y RalstonRebecca J AbergelPublished in: Journal of the American Chemical Society (2022)
Rare-earth elements, which include the lanthanide series, are key components of many clean energy technologies, including wind turbines and photovoltaics. Because most of these 4f metals are at high risk of supply chain disruption, the development of new recovery technologies is necessary to avoid future shortages, which may impact renewable energy production. This paper reports the synthesis of a non-natural biogenic material as a potential platform for bioinspired lanthanide extraction. The biogenic material takes advantage of the atomically precise structure of a 2D crystalline protein lattice with the high lanthanide binding affinity of hydroxypyridinonate chelators. Luminescence titration data demonstrated that the engineered protein layers have affinities for all tested lanthanides in the micromolar-range (dissociation constants) and a higher binding affinity for the lanthanide ions with a smaller ionic radius. Furthermore, competitive titrations confirmed the higher selectivity (up to several orders of magnitude) of the biogenic material for lanthanides compared to other cations commonly found in f-element sources. Lastly, the functionalized protein layers could be reused in several cycles by desorbing the bound metal with citrate solutions. Taken together, these results highlight biogenic materials as promising bioadsorption platforms for the selective binding of lanthanides, with potential applications in the recovery of these critical elements from waste.
Keyphrases
- binding protein
- single molecule
- protein protein
- energy transfer
- quantum dots
- amino acid
- metal organic framework
- emergency department
- human health
- machine learning
- dna binding
- ionic liquid
- risk assessment
- drinking water
- room temperature
- heavy metals
- big data
- climate change
- transcription factor
- current status
- tissue engineering
- deep learning
- municipal solid waste
- molecularly imprinted
- health risk